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Databricks releases, every cloud

50 releases of 1321

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  1. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

  2. You can now use custom base environments for Python, Python Wheels, and notebook tasks in serverless jobs

    Defined with YAML files, they support Python, Python wheel, and notebook tasks.

  3. Login required to download ODBC driver

    Requires login and license acceptance, except for AWS GovCloud which needs account team access.

  4. Serverless compute is now available in Azure China North 3

    Available for notebooks, jobs, pipelines, and SQL warehouses.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  5. Serverless workspaces are now available in new GCP regions

    Available in most GCP regions, see documentation for list.

    AWS(not on this cloud)Azure(not on this cloud)GCP, read it on their docsSAP(unknown)
  6. Serverless compute is now available in new regions

    Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.

    AWS(not on this cloud)Azure, read it on their docsGCP(not on this cloud)SAP(unknown)
  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

  9. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

  10. The billable usage table now records the performance mode of serverless jobs and pipelines

    Records performance mode in product_features.performance_target column with values PERFORMANCE_OPTIMIZED, STANDARD, or null.

  11. Admins can now manage a workspace's serverless base environments (Public Preview)

    Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.

Headlines, dates and product areas are Databricks' own, from the release notes published for each cloud, and every item links to the note it came from. The one-line summaries are ours. Not a Databricks product and not affiliated with Databricks, Inc.